Automated assessment of FDG-PET for differential diagnosis in patients with neurodegenerative disorders.

PURPOSE: To review literature until November 2015 and reach a consensus on whether automatic semi-quantification of brain FDG-PET is useful in the clinical setting for neurodegenerative disorders. METHODS: A literature search was conducted in Medline, Embase, and Google Scholar. Papers were selected with a lower limit of 30 patients (no limits with autopsy confirmation). Consensus recommendations were developed through a Delphi procedure, based on the expertise of panelists, who were also informed about the availability and quality of evidence, assessed by an independent methodology team. RESULTS: Critical outcomes were available in nine among the 17 papers initially selected. Only three papers performed a direct comparison between visual and automated assessment and quantified the incremental value provided by the latter. Sensitivity between visual and automatic analysis is similar but automatic assessment generally improves specificity and marginally accuracy. Also, automated assessment increases diagnostic confidence. As expected, performance of visual analysis is reported to depend on the expertise of readers. CONCLUSIONS: Tools for semi-quantitative evaluation are recommended to assist the nuclear medicine physician in reporting brain FDG-PET pattern in neurodegenerative conditions. However, heterogeneity, complexity, and drawbacks of these tools should be known by users to avoid misinterpretation. Head-to-head comparisons and an effort to harmonize procedures are encouraged.

pFDR and pFNR estimation for brain networks construction.

Recent developments in the study of brain functional connectivity are widely based on graph theory. In the current analysis of brain networks, there is no unique way to derive the adjacency matrix, which is a useful representation for a graph. Its entries, containing information about the existence of links, are identified by thresholding the correlation between the time series that characterized the dynamic behavior of the nodes. In this work, we put forward a strategy to choose a suitable threshold on the correlation matrix considering the problem of multiple comparisons in order to control the error rates. In this context we propose to control the positive false discovery rate (pFDR) and a similar measure involving false negatives, called the positive false nondiscovery rate (pFNR). In particular, we provide point and interval estimators for pFNR and a method for balancing the two types of error, demonstrating it by using functional magnetic resonance imaging data and Monte Carlo simulations.

Assessment of system dysfunction in the brain through MRI-based connectomics.

Network-based analysis of structural and functional connections has provided a new technique to study the brains of healthy people and patients with neurological and psychiatric disorders. Graph theory provides a powerful method to quantitatively describe the topological organisation of brain connectivity. With such a framework, the brain can be depicted as a set of nodes connected by edges. Distinct modifications of network topological organisation in the brain have been identified during development and normal ageing, whereas disrupted functional and structural connectivities have been associated with several neurological and psychiatric disorders, including dementia, amyotrophic lateral sclerosis, multiple sclerosis, and schizophrenia. These assessments have improved understanding of the clinical manifestations noted in these patients, including disability and cognitive impairment. Future network-based research might enable indentification of different stages of disorders, subtypes for cognitive impairment, and connectivity profiles associated with different clinical outcomes.

Assessment of brain white matter fiber bundle atrophy in patients with Friedreich ataxia.

PURPOSE: To investigate in vivo severity and topographic distribution of brain white matter (WM) fiber bundle atrophy in patients with Friedreich ataxia, a condition characterized by an uneven involvement of brain WM, and to correlate such findings with the clinical status of the patients. MATERIALS AND METHODS: The study was conducted with institutional review board approval. Written informed consent was obtained from each participant. Sixteen patients with Friedreich ataxia and 15 healthy control subjects were studied by using a 1.5-T magnetic resonance (MR) imager and 3-mm-thick diffusion-tensor images with 15 noncollinear directions. The size of WM fiber bundles was examined at a voxel level by using a recently developed method, which relies on production of anisotropy maps and nonlinear registration. Data were analyzed by using statistical parametric mapping software and an analysis of covariance model adjusted for age and sex. RESULTS: Compared with control subjects, patients with Friedreich ataxia had WM atrophy in (a) the central portion of the medulla oblongata, (b) the dorsal upper pons, (c) the superior cerebellar peduncles, (d) the central portion of the midbrain, (e) the medial portion of the right cerebral peduncle, (f) the peridentate region, bilaterally, and (g) the optic chiasm. The severity of the neurologic deficits correlated significantly with atrophy of the peridentate WM, bilaterally, and that of the superior cerebellar peduncle decussation. CONCLUSION: Findings of this study show that it is feasible to obtain in vivo atrophy estimates of specific brain WM fiber bundles in patients with Friedreich ataxia and that such estimates correlate with patients' clinical status. This approach has the potential to provide new information that is likely to improve the understanding of the pathophysiology of inherited ataxias.

Assessment of white matter tract damage in mild cognitive impairment and Alzheimer's disease.

Diffusion tensor MRI-based tractography was used to investigate white matter (WM) changes in the major limbic (i.e., fornix and cingulum) and cortico-cortical association pathways [i.e., the uncinate fasciculus, the inferior fronto-occipital fasciculus, the inferior longitudinal fasciculus (ILF), the superior longitudinal fasciculus, and the corpus callosum] in 25 Alzheimer's disease (AD) patients, 19 amnestic mild cognitive impairment (aMCI) patients, and 15 healthy controls (HC). Mean diffusivity (MD), fractional anisotropy (FA), as well as axial (DA) and radial (DR) diffusivities were measured for each tract, using an atlas-based tractography approach. The association of WM tract integrity with hippocampal volume was also assessed. MD values were significantly different among groups in all WM tracts (P values ranging from 0.002 to 0.03), except in the fornix (P = 0.06) and the inferior fronto-occipital fasciculus (P = 0.09). Conversely, FA was significantly different among groups in the fornix only (P = 0.02). DA values were significantly different among groups in all WM tracts (P values ranging from 0.001 to 0.01), except in the fornix (P = 0.13) and the cingulum (P = 0.29). Significantly different DR values among groups were found in the fornix (P = 0.02) and the ILF (P = 0.01). In the fornix and cingulum, DR was significantly more increased than DA in both patient groups compared to HC. No difference in DA versus DR was found in cortico-cortical WM tracts. DA values in the fornix were significantly correlated with the hippocampal volume. This study demonstrates a different pattern of WM involvement in the limbic and cortico-cortical association pathways in aMCI and AD patients.

Longitudinal assessment of grey matter contraction in amyotrophic lateral sclerosis: A tensor based morphometry study.

Our objective was to investigate grey matter (GM) contraction in patients with amyotrophic lateral sclerosis (ALS) using tensor based morphometry (TBM). Using a 1.5 Tesla scanner, T1-weighted MRI scans were obtained at baseline and at follow-up (mean interval, 9 months) from 16 ALS and 10 controls. Standard TBM procedures in Statistical Parametric Mapping (SPM2) were used for image processing and statistical analyses. The frontotemporal cortex and basal ganglia were considered areas of interest, based on pathological studies. Eight patients showed rapid clinical progression of ALS during the follow-up period. Compared to controls, all ALS patients showed progression of GM atrophy in left premotor cortex and right basal ganglia. Patients with rapidly progressing ALS showed GM atrophy changes in a larger motor cortical-subcortical area and in extramotor frontal regions compared to both controls and to non-rapidly progressing cases. Thus, TBM detected longitudinal atrophy changes in the motor network in ALS occurring over less than one year. The faster the clinical progression, the greater was the GM loss in motor and prefrontal areas. Further advances in tracking longitudinal changes in cortical and subcortical regions in ALS may provide an objective marker for monitoring disease progression, and the disease-modifying effect of potential treatments.